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CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes

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Abstract

Purpose

The purpose of the study was to determine if CT texture features of untreated hepatic metastatic colorectal cancer (CRC) relate to pathologic features and clinical outcomes.

Methods

Tumor texture analysis was performed on single hepatic metastatic lesions on pre-treatment contrast-enhanced CT scans in 77 pts (mean age 58, 34F/43M) using a novel tool. Measures of heterogeneity, including entropy, kurtosis, skewness, mean, mean positive pixels (MPP), and standard deviation (SD) of pixel distribution histogram were derived with filter values corresponding to fine (spatial scaling factor (ssf) 2), medium (ssf 3, 4), and coarse textures (ssf 5, 6). Texture parameters were correlated with tumor grade, baseline serum CEA, and KRAS mutation status. Overall survival was also correlated using Cox proportional hazards models. Single-slice 2D vs. whole-tumor volumetric 3D texture analysis was compared in a subcohort of 20 patients.

Results

Entropy, MPP, and SD at medium filtration levels were significantly associated with tumor grade (MPP ssf 3 P = 0.002, SD ssf 3 P = 0.004, entropy ssf 4 P = 0.007). Skewness was negatively associated KRAS mutation (P = 0.02). Entropy at coarse filtration levels was associated with survival (Hazard ratio (HR) for death 0.65, 95% CI 0.44–0.95, P = 0.03). Texture results for 2D and 3D analysis were similar.

Conclusions

CT texture features, particularly entropy, MPP, and SD, are significantly associated with tumor grade in untreated CRC liver metastases. Tumor entropy at coarse filters correlates with overall survival. Single-slice 2D texture analysis appears to be adequate.

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Disclosures

Dr. Pickhardt co-founded VirtuoCTC, is a shareholder in Cellectar Biosciences, and is a consultant for Check-Cap.

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Authors and Affiliations

  1. Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3/311 Clinical Sciences Center, 600 Highland Ave, Madison, WI, 53792, USA

    Meghan G. Lubner, Nicholas Stabo, Alejandro Munoz del Rio & Perry J. Pickhardt

  2. Department of Internal Medicine (Sections Human Oncology and Gastroenterology), University of Wisconsin School of Medicine and Public Health, Madison, WI, USA

    Sam J. Lubner & Richard B. Halberg

  3. Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA

    Alejandro Munoz del Rio & Chihwa Song

Authors
  1. Meghan G. Lubner
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  2. Nicholas Stabo
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Correspondence to Meghan G. Lubner.

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Lubner, M.G., Stabo, N., Lubner, S.J. et al. CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes. Abdom Imaging 40, 2331–2337 (2015). https://doi.org/10.1007/s00261-015-0438-4

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  • DOI: https://doi.org/10.1007/s00261-015-0438-4

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